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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Iterative demodulation and decoding of coded non-square QAM

Simulation results show that, with iterative demodulation and decoding, coded NS-8QAM performs 0.5 dB better than standard 8QAM and 0.7 dB better than 8PSK at BER= 10(sup -5), when the FEC code is the (15, 11) Hamming code concatenated with a rate-1 accumulator code, while coded NS-32QAM performs 0.25 dB better than standard 32QAM.

iterative decoding QAM bit error rate capacity↗
NASA NTRS1997

(abstract) Case Study of the Design of a Viterbi Decoder

This paper describes the design of an ASIC performing the Viterbi decoder function with a constraint length of 15 and at a speed of 4.4 Mb/s. The architecture of the chip is described, as well as the design challenges which were overcome. The author also describes the successful application of the design system.

Viterbi decoders ASIC chip architecture constraint↗
NASA NTRS1997

Case Study of the Design of a Viterbi Decoder

This paper describes the design of an ASIC performing the Viterbi decoder function with a constraint length of 15 and a speed of 4.4 Mb/s. The architecture of the chip is described, as well as the design challenges which were overcome. The author also describes the successful application of the design system.

Viterbi decoder ASIC microprocessor design↗
NASA NTRS2008

Information-reduced Carrier Synchronization of Iterative Decoded BPSK and QPSK using Soft Decision (Extrinsic) Feedback

This paper addresses the carrier-phase estimation problem under low SNR conditions as are typical of turbo- and LDPC-coded applications. In previous publications by the first author, closed-loop carrier synchronization schemes for error-correction coded BPSK and QPSK modulation were proposed that were based on feeding back hard data decisions at the input of the loop, the purpose being to remove the modulation prior to attempting to track the carrier phase as opposed to the more conventional decision-feedback schemes that incorporate such feedback inside the loop. In this paper, we consider an alternative approach wherein the extrinsic soft information from the iterative decoder of turbo or LDPC codes is instead used as the feedback.

carrier synchronization↗
DOE OSTI2025

Decoding Antenna Behavior in Metal—Organic Frameworks

Metal–organic frameworks (MOFs) define a solid-state platform for developing artificial photosystems. Efficient anisotropic exciton migrations in these frameworks entail “antenna behavior” that can power up the distal interior reaction centers (RC), driving charge separation between donor-acceptor pairs. Reminiscent of the natural light-harvesting complex, such processes can achieve high quantum yield by exploiting the vast interior surface of the porous crystallites. It is important to understand the optimum positioning of the RC site relative to the anisotropic exciton migration path within these frameworks. The efficiency of such antenna behavior is probed here through Stern–Volmer (SV) type analysis with a series of node-anchored redox quenchers, ferrocene-carboxylate, ferrocene acetate, and dinitrobenzoate. Decoding various intrinsic processes, this work constructs a revised SV formalism in solid assembly that hosts ultrafast anisotropic exciton migration to account for the intrinsic exciton hopping rate from the extrinsic electron transfer rate, and the dimension of effective quenching. In conclusion, this transformative understanding can be applied to other relevant solid-state assemblies.

Saha, Bapan [Southern Illinois University, Carbond↗
DOE OSTI2023

Long–short-term memory encoder–decoder with regularized hidden dynamics for fault detection in industrial processes

The ability of recurrent neural networks (RNN) to model nonlinear dynamics of high dimensional process data has enabled data-driven RNN-based fault detection algorithms. Previous studies have focused on detecting faults by identifying the discrepancies in data distribution between the faulty and normal data, as reflected in prediction errors generated by RNN models. However, in industrial processes, variations in data distribution can also result from changes in normal control setpoints and compensatory control adjustments in response to disturbances, making it hard to differentiate between normal and faulty conditions. This paper proposes a fault detection method utilizing a long short-term memory (LSTM) encoder–decoder structure with regularized hidden dynamics and reversible instance normalization (RevIN) to compactly represent high-dimensional measurements for effective monitoring. During training, the hidden states of the model are regularized to form a low-dimensional latent space representation of the original multivariate time series data. As a result, the prediction errors of the latent states can be used to monitor the abnormal dynamic variations, while the reconstruction errors of the measured variables are used to monitor the abnormal static variations. Furthermore, the proposed indices can reflect operating conditions, even when the distribution of test data changes, which helps distinguish faults from normal adjustments and disturbances that controllers can settle. Here, data from numerical simulation and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed fault detection method.

42 ENGINEERING↗